reelier
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| reelier_scanA | Discover replayable workflows in an agent's session history (defaults to ~/.claude/projects). Returns each session's transcript path — feed one to reelier_from_session. Only MCP/HTTP tool-call sequences are replayable; native file/shell actions are reported as skipped, never fabricated into a fake result. USE WHEN: deciding which past work is worth compiling into a replayable skill. |
| reelier_from_sessionA | Compile a SKILL.md from a session transcript. USE WHEN: the work ALREADY happened (this session or by hand) — recording can't be retroactive. NOT for work that hasn't happened yet (record that live via the reelier mcp proxy). Get the transcriptPath from reelier_scan first. Returns the written skill's path, stats, and open questions — or, honestly, that nothing in the transcript was replayable. If the workflow used a relative time window ("this week"), bind it to a date variable (e.g. {{today-7d}}) so later replays pull the CURRENT window, not a frozen one — the openQuestions output flags this. |
| reelier_replayA | Run a skill file at Level 0 (deterministic replay, zero LLM calls) and return the real run record: per-step outcomes, timing, totals, and — when a step drifted — why (the failing assertion). Never fabricates a pass. Reproduces the recorded TOOL CALLS (MCP/HTTP) only — no LLM reasoning or prose step re-runs. It does NOT schedule itself: pair with cron/CI for recurring runs. Pass vars to fill {{templated}} inputs (e.g. a computed date window) so a replay pulls current data. READ-ONLY by default: 'idempotent-write' steps are held back (reported as a refused/failed step) unless you pass allowWrites — so replaying never re-fires a write. |
| reelier_pushA | Push a skill's local run records (and, on first push, the skill file) to your receipt ledger, where each receipt gets a shareable permalink + verified-replay badge. Requires an apiKey — from |
| reelier_diffA | Compare two runs of the same skill and report SAME or DRIFTED — the drift-detector for a recorded baseline replayed on a schedule. Compares per-step outcomes, structure, and heal-level from .reelier/runs/.jsonl (defaults to the last two runs); data values that legitimately change run-to-run are NOT drift. Drifted steps carry why (the failing assertion). To check a MODEL upgrade: re-record the workflow with the new model, then diff against your frozen baseline — replaying a pinned skill can't reveal model changes (replay never calls a model). Honest when there aren't two runs yet. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: scan discovers workflows, from_session compiles them into skills, replay executes skills, push shares receipts, and diff compares runs. No overlap or confusion.
All tools share the 'reelier_' prefix followed by a clear verb or action (scan, replay, push, from_session, diff). The pattern is consistent and intuitive.
Five tools is a well-scoped set for the domain of replayable skill management. Each tool serves a core function without redundancy or excess.
The tool surface covers scanning, compiling, replaying, sharing, and comparing skills. However, there is a notable gap: live recording of workflows is mentioned but not provided as a tool, which limits the server's ability to create new skills from scratch.